The impact of hospital accreditation on clinical documentation compliance: a life cycle explanation using interrupted time series analysis.
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ABSTRACT: Objective
To evaluate whether accredited hospitals maintain quality and patient safety standards over the accreditation cycle by testing a life cycle explanation of accreditation on quality measures. Four distinct phases of the accreditation life cycle were defined based on the Joint Commission International process. Predictions concerning the time series trend of compliance during each phase were specified and tested.Design
Interrupted time series (ITS) regression analysis of 23 quality and accreditation compliance measures.Setting
A 150-bed multispecialty hospital in Abu Dhabi, UAE.Participants
Each month (over 48 months) a simple random sample of 24% of patient records was audited, resulting in 276,000 observations collected from 12,000 patient records, drawn from a population of 50,000.Interventions
The impact of hospital accreditation on the 23 quality measures was observed for 48 months, 1 year preaccreditation (2009) and 3-year postaccreditation (2010-2012).Main outcome measures
The Life Cycle Model was evaluated by aggregating the data for 23 quality measures to produce a composite score (YC) and fitting an ITS regression equation to the unweighted monthly mean of the series.Results
The four phases of the life cycle are as follows: the initiation phase, the presurvey phase, the postaccreditation slump phase and the stagnation phase. The Life Cycle Model explains 87% of the variation in quality compliance measures (R(2)=0.87). The ITS model not only contains three significant variables (β1, β2 and β3) (p≤0.001), but also the size of the coefficients indicates that the effects of these variables are substantial (β1=2.19, β2=-3.95 (95% CI -6.39 to -1.51) and β3=-2.16 (95% CI -2.52 to -1.80).Conclusions
Although there was a reduction in compliance immediately after the accreditation survey, the lack of subsequent fading in quality performance should be a reassurance to researchers, managers, clinicians and accreditors.
SUBMITTER: Devkaran S
PROVIDER: S-EPMC4127940 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China. We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models. Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%). Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.
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Project description:BackgroundThere is widespread concern over the impact of public health measures, such as lockdowns, associated with COVID-19 on mental health, including suicide. High-quality evidence from low-income and middle-income countries, where the burden of suicide and self-harm is greatest, is scarce. We aimed to determine the effect of the pandemic on hospital presentations for self-poisoning.MethodsIn this interrupted time-series analysis, we established a new self-poisoning register at the tertiary care Teaching Hospital Peradeniya in Sri Lanka, a lower-middle-income country. Using a standard extraction sheet, data were gathered for all patients admitted to the Toxicology Unit with self-poisoning between Jan 1, 2019, and Aug 31, 2020. Only patients classified by the treating clinician as having intentionally self-poisoned were included. Data on date of admission, age or date of birth, sex, and poisoning method were collected. No data on ethnicity were available. We used interrupted time-series analysis to calculate weekly hospital admissions for self-poisoning before (Jan 1, 2019-March 19, 2020) and during (March 20-Aug 31, 2020) the pandemic, overall and by age (age <25 years vs ≥25 years) and sex. Individuals with missing date of admission were excluded from the main analysis.FindingsBetween Jan 1, 2019, and Aug 31, 2020, 1401 individuals (584 [41·7%] males, 761 [54·3%] females, and 56 [4·0%] of unknown sex) presented to the hospital with self-poisoning and had date of admission data. A 32% (95% CI 12-48) reduction in hospital presentations for self-poisoning in the pandemic period compared with pre-pandemic trends was observed (rate ratio 0·68, 95% CI 0·52-0·88; p=0·0032). We found no evidence that the impact of the pandemic differed by sex (rate ratio 0·64, 95% CI 0·44-0·94, for females vs 0·85, 0·57-1·26, for males; pinteraction=0·43) or age (0·64, 0·44-0·93, for patients aged <25 years vs 0·81, 0·57-1·16, for patients aged ≥25 years; pinteraction=0·077).InterpretationThis is the first study from a lower-middle-income country to estimate the impact of the pandemic on self-harm (non-fatal) accounting for underlying trends. If the fall in hospital presentations during the pandemic reflects a reduction in the medical treatment of people who have self-poisoned, rather than a true fall in incidence, then public health messages should emphasise the importance of seeking help early.FundingElizabeth Blackwell Institute University of Bristol, Wellcome Trust, and Centre for Pesticide Suicide Prevention.TranslationsFor the Sinhalese and Tamil translations of the abstract see Supplementary Materials section.
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Project description:BackgroundThe Government of Ontario, Canada, announced hospital funding reforms in 2011, including Quality-based Procedures (QBPs) involving pre-set funds for managing patients with specific diagnoses/procedures. A key goal was to improve quality of care across the jurisdiction.MethodsInterrupted time series evaluated the policy change, focusing on four QBPs (congestive heart failure, hip fracture surgery, pneumonia, prostate cancer surgery), on patients hospitalized 2010-2017. Outcomes included return to hospital or death within 30 days, acute length of stay (LOS), volume of admissions, and patient characteristics.ResultsAt 2 years post-QBPs, the percentage of hip fracture patients who returned to hospital or died was 3.13% higher in absolute terms (95% CI: 0.37% to 5.89%) than if QBPs had not been introduced. There were no other statistically significant changes for return to hospital or death. For LOS, the only statistically significant change was an increase for prostate cancer surgery of 0.33 days (95% CI: 0.07 to 0.59). Volume increased for congestive heart failure admissions by 80 patients (95% CI: 2 to 159) and decreased for hip fracture surgery by 138 patients (95% CI: -183 to -93) but did not change for pneumonia or prostate cancer surgery. The percentage of patients who lived in the lowest neighborhood income quintile increased slightly for those diagnosed with congestive heart failure (1.89%; 95% CI: 0.51% to 3.27%) and decreased for those who underwent prostate cancer surgery (-2.08%; 95% CI: -3.74% to -0.43%).InterpretationThis policy initiative involving a change to hospital funding for certain conditions was not associated with substantial, jurisdictional-level changes in access or quality.
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Project description:BackgroundCities globally have started to make substantial investment in more sustainable forms of transportation. We aimed to evaluate whether the construction of new cycling infrastructure in Paris and Lyon, France, affected population cycling activity along new or improved routes.MethodsRoutinely collected cycle count data from January 2014 to March 2020 were acquired for the cities of Paris and Lyon. Improvements were identified at 15 locations with 6 months of pre- and post-intervention data. Comparison streets were chosen within Paris or Lyon for which pre-intervention trends in cycling were similar to those at intervention sites. Controlled interrupted time series analyses and autocorrelation were performed adjusting for seasonality. Random-effects meta-analysis combined results across streets within each city and overall.ResultsOn average, cycling counts/day increased on both intervention and control streets in Paris and Lyon. In general, results of the ITS analysis indicated no significant change in the level or trend as a result of the improvements in either city. Meta-analysis suggested that intervention streets in Paris had a larger positive pooled effect size for level change (218 cycle counts, 95% CI -189, 626, I2 = 0%) compared to Lyon (34, 95% CI -65, 133, I2 = 14%); however, confidence intervals for both cities were wide and included no effect.ConclusionsThe findings suggest that improving or constructing new cycle lanes may be necessary but not sufficient to induce significant changes in cycling levels. There is a need to understand how context, intervention design and other complementary interventions can improve the effectiveness of new cycling infrastructure.
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Project description:IntroductionInterrupted Time Series (ITS) studies may be used to assess the impact of an interruption, such as an intervention or exposure. The data from such studies are particularly amenable to visual display and, when clearly depicted, can readily show the short- and long-term impact of an interruption. Further, well-constructed graphs allow data to be extracted using digitizing software, which can facilitate their inclusion in systematic reviews and meta-analyses.AimWe provide recommendations for graphing ITS data, examine the properties of plots presented in ITS studies, and provide examples employing our recommendations.Methods and resultsGraphing recommendations from seminal data visualization resources were adapted for use with ITS studies. The adapted recommendations cover plotting of data points, trend lines, interruptions, additional lines and general graph components. We assessed whether 217 graphs from recently published (2013-2017) ITS studies met our recommendations and found that 130 graphs (60%) had clearly distinct data points, 100 (46%) had trend lines, and 161 (74%) had a clearly defined interruption. Accurate data extraction (requiring distinct points that align with axis tick marks and labels that allow the points to be interpreted) was possible in only 72 (33%) graphs.ConclusionWe found that many ITS graphs did not meet our recommendations and could be improved with simple changes. Our proposed recommendations aim to achieve greater standardization and improvement in the display of ITS data, and facilitate re-use of the data in systematic reviews and meta-analyses.
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Project description:OBJECTIVES:To identify whether the abolition of prescription fees in Scotland resulted in: (1) Increase in the number (cost to NHS) of medicines prescribed for which there had been a fee (inhaled corticosteroids). (2) Reduction in hospital admissions for conditions related to those medications for which there had been a fee (asthma or chronic obstructive pulmonary disease (COPD))-when both are compared with prescribed medicines and admissions for a condition (diabetes mellitus) for which prescriptions were historically free. DESIGN:Natural experimental retrospective general practice level interrupted time series (ITS) analysis using administrative data. SETTING:General practices, Scotland, UK. PARTICIPANTS:732 (73.6%) general practices across Scotland with valid dispensed medicines and hospital admissions data during the study period (July 2005-December 2013). INTERVENTION:Reduction in fees per dispensed item from April 2008 leading to the abolition of the fee in April 2011, resulting in universal free prescriptions. PRIMARY AND SECONDARY OUTCOMES:Hospital admissions recorded in the Scottish Morbidity Record - 01 Inpatient (SMR01) and dispensed medicines recorded in the Prescribing Information System (PIS). RESULTS:The ITS analysis identified marked step reductions in adult (19-59 years) admissions related to asthma or COPD (the intervention group), compared with older or young people with the same conditions or adults with diabetes mellitus (the counterfactual groups). The prescription findings were less coherent and subsequent sensitivity analyses found that both the admissions and prescriptions data were highly variable above the annual or seasonal level, limiting the ability to interpret the findings of the ITS analysis. CONCLUSIONS:This study did not find sufficient evidence that universal free prescriptions was a demonstrably effective or ineffective policy, in terms of reducing hospital admissions or reducing socioeconomic inequality in hospital admissions, in the context of a universal, publicly administered medical care system, the National Health Service of Scotland.
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Project description:BackgroundUncontrolled infection and lockdown measures introduced in response have resulted in an unprecedented challenge for health systems internationally. Whether such unprecedented impact was due to lockdown itself and recedes when such measures are lifted is unclear. We assessed the short- and medium-term impacts of the first lockdown measures on hospital care for tracer non-COVID-19 conditions in England, Scotland and Wales across diseases, sexes, and socioeconomic and ethnic groups.MethodsWe used OpenSAFELY (for England), EAVEII (Scotland), and SAIL Databank (Wales) to extract weekly hospital admission rates for cancer, cardiovascular and respiratory conditions (excluding COVID-19) from the pre-pandemic period until 25/10/2020 and conducted a controlled interrupted time series analysis. We undertook stratified analyses and assessed admission rates over seven months during which lockdown restrictions were gradually lifted.FindingsOur combined dataset included 32 million people who contributed over 74 million person-years. Admission rates for all three conditions fell by 34.2% (Confidence Interval (CI): -43.0, -25.3) in England, 20.9% (CI: -27.8, -14.1) in Scotland, and 24.7% (CI: -36.7, -12.7) in Wales, with falls across every stratum considered. In all three nations, cancer-related admissions fell the most while respiratory-related admissions fell the least (e.g., rates fell by 40.5% (CI: -47.4, -33.6), 21.9% (CI: -35.4, -8.4), and 19.0% (CI: -30.6, -7.4) in England for cancer, cardiovascular-related, and respiratory-related admissions respectively). Unscheduled admissions rates fell more in the most than the least deprived quintile across all three nations. Some ethnic minority groups experienced greater falls in admissions (e.g., in England, unscheduled admissions fell by 9.5% (CI: -20.2, 1.2) for Whites, but 44.3% (CI: -71.0, -17.6), 34.6% (CI: -63.8, -5.3), and 25.6% (CI: -45.0, -6.3) for Mixed, Other and Black ethnic groups respectively). Despite easing of restrictions, the overall admission rates remained lower in England, Scotland, and Wales by 20.8%, 21.6%, and 22.0%, respectively when compared to the same period (August-September) during the pre-pandemic years. This corresponds to a reduction of 26.2, 23.8 and 30.2 admissions per 100,000 people in England, Scotland, and Wales respectively.InterpretationHospital care for non-COVID diseases fell substantially across England, Scotland, and Wales during the first lockdown, with reductions persisting for at least six months. The most deprived and minority ethnic groups were impacted more severely.FundingThis work was funded by the Medical Research Council as part of the Lifelong Health and Wellbeing study as part of National Core Studies (MC_PC_20030). SVK acknowledges funding from the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE - The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. BG has received research funding from the NHS National Institute for Health Research (NIHR), the Wellcome Trust, Health Data Research UK, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme.
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